Hugging Face's logo

Datasets:
taejoon89
/
openpath-corpus

Tasks:
Image Feature Extraction
Size:
n>1T
Tags:
pathology
histopathology
whole-slide-imaging
digital-pathology
self-supervised
webdataset
Libraries:
WebDataset
License:
Dataset card Data Studio Files
xet
 Community
openpath-corpus
File size: 4,681 Bytes
606d0f4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e63bd2e
606d0f4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
---
license: other
license_name: mixed-public-cc-by-cc0-nih-open
pretty_name: OpenPath Corpus
tags:
  - pathology
  - histopathology
  - whole-slide-imaging
  - digital-pathology
  - self-supervised
  - webdataset
task_categories:
  - image-feature-extraction
size_categories:
  - n>1T
extra_gated_prompt: >-
  Access is granted for research use. By requesting access you agree to (1) cite the
  OpenPath paper and this corpus, and (2) respect the original license and attribution
  terms of every source dataset listed below (in particular the TCGA and GTEx attribution
  statements). The corpus redistributes only public, redistributable pathology data.
extra_gated_fields:
  Name: text
  Affiliation: text
  Intended use: text
  I agree to the source-dataset license and attribution terms: checkbox
---

# OpenPath Corpus

Public-only whole-slide histopathology **tile corpus** used to pre-train
**[OpenPath](https://huggingface.co/taejoon89/openpath)**, a ViT-g/14 pathology foundation model.
Tiles are re-extracted at **native ~40× (0.5 µm-per-pixel)**, which is the data lever that lets
OpenPath rank **#1 on the contamination-free AMC-HCC-ST benchmark among seven foundation models**
(see the [code / model card](https://huggingface.co/taejoon89/openpath)).

## Contents

- **33,991 WebDataset shards** (`.tar`), **~17 TB**, **~834 M tiles**, 224×224 at native 40×.
- Seven public sources (sharded into slots such as `tcga_s0…s5`):

| Source | Shards | License | Notes |
|---|---|---|---|
| **TCGA** (`tcga_s0…s5`) | 20,589 | NIH / GDC open-access tier | attribution required (see below) |
| **GTEx** (`gtex_s0…s1`) | 4,965 | GTEx Portal permissive (attribution-only); CC-BY 4.0 DICOM mirror available | attribution required |
| **TCIA** (`tcia_s0…s1`) | 3,891 | CC-BY 3.0 / 4.0 (collection-specific) | pathology collections |
| **ACROBAT** | 3,318 | CC-BY 4.0 | breast H&E + IHC |
| **CAMELYON16/17** | 784 | CC0 (public domain) | breast lymph node |
| **SurGen** | 426 | CC-BY 4.0 | colorectal |
| **MIDOG** (2021 / 2022 / ++) | 18 | CC-BY 4.0 | multi-tumor |
| **Total** | **33,991** | mixed public / redistributable | commercial use permitted |

All sources are commercial-use-permitted (CC-BY / CC0 / NIH-open). This corpus does **not** include
any non-commercial (NC) data. PCam / CAMELYON overlap standard patch benchmarks and are therefore
excluded from OpenPath's evaluation.

## Format & loading

- **Layout:** `<source>/tiles/shards/w<id>/*.tar` (WebDataset). Each tar entry is a JPEG tile with a
  JSON sidecar (`wsi_id`, tile coordinates, magnitude).
- **Training glob:** `*/tiles/shards/w*/*.tar`.

```python
import webdataset as wds
url = "path/to/openpath-corpus/tcga_s0/tiles/shards/w0/000000.tar"
ds = wds.WebDataset(url).decode("pil").to_tuple("jpg", "json")
for img, meta in ds:
    ...  # img: 224×224 PIL RGB, meta: {wsi_id, x, y, mag, ...}
```

## Access & terms (gated)

Gated, manual approval. For research use. When you use the corpus, **cite the OpenPath paper** and
**preserve each source's attribution**, e.g.:

> The results shown here are in whole or part based upon data generated by the TCGA Research Network:
> https://www.cancer.gov/tcga.
>
> Data were obtained from the GTEx Portal (and/or dbGaP accession phs000424).

## Related artifacts

| Artifact | Hugging Face repo | Notes |
|---|---|---|
| **Corpus** | `taejoon89/openpath-corpus` | This repository |
| **Checkpoints** | `taejoon89/openpath-checkpoints` | teacher checkpoints (`training_0` … `training_345000`); released = `training_316250` |
| **Code** | `taejoon89/openpath` | training & evaluation code (also on [GitHub](https://github.com/taejoon89/openpath)) |

## Citation

```bibtex
@misc{openpath2026,
  title  = {OpenPath: Public-Data Pathology Foundation Models and Leakage-Free Evaluation},
  author = {Tae Joon Jun},
  year   = {2026},
  note   = {https://huggingface.co/taejoon89/openpath}
}
```

## Acknowledgements

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea
Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of
Korea (grant number: HR21C0198); the Advanced GPU Utilization Support Program funded by the Government
of the Republic of Korea, Ministry of Science and ICT; and the National Research Foundation of Korea
(NRF) grant funded by the Korean government (MSIT) (grant number: RS-2026-25522634).

## License

The corpus redistributes public pathology datasets under their original **CC-BY / CC0 / NIH-open**
terms (all redistributable, commercial use permitted). See the per-source table above and cite/attribute
each source accordingly.